In-Memory MemSQL Database Adds JSON Real-Time Analytics

MemSQL's real-time, big data analytics platform is the first to combine structured and semi-structured data into a single database.

Database administrators using or researching in-memory systems may be interested to know about this industry update.
MemSQL announced Sept. 18 that its distributed in-memory database, which competes with similar DBs from SAP, SAS, Teradata, Oracle, Birst and several others, has become the first to provide Java Script Object Notation (JSON) analytics. JSON brings a consolidated view across structured and semi-structured data—including standard enterprise and social media data.
As a result, organizations for the first time can harness and combine two disparate data sources for operational analytics, network security, real-time recommendations and risk management.
JSON has become a popular syntax for storing and exchanging semi-structured data from social media networks such as Facebook, Twitter and Instagram. However, this information has been largely untapped as it relates to an enterprise's structured data, leaving companies with siloed views into their entire customer bases.

NoSQL databases support JSON and the querying and parsing of JSON structures but do little in the way of real-time analytics. Complicating matters is the fact that SQL has no native support for JSON, which makes it difficult to query data across these popular data types. This lack of integration significantly limits an organization's ability to maximize the power of real-time big data analytics.

"Based on our 2012 end-user research, speed of response and utilization of multi-structured data types such as JSON are important in the world of big data," said John Myers, senior analyst at Enterprise Management Associates, a Boulder, Colo.-based analysis firm. "MemSQL adding true SQL-based access to JSON promises to bring analytical response to multi-structured datasets in a way that will be difficult to match."
Enterprises such as Zynga, Morgan Stanley and Shutterstock are using MemSQL in production environments, which are capable of supporting thousands of nodes and hundreds of terabytes of data.
MemSQL is available for download here.